S&P 500

Clase series de tiempo, primavera 2024

Datos

library(tidyquant)

Loading required package: lubridate

Attaching package: ‘lubridate’

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Loading required package: PerformanceAnalytics
Loading required package: xts
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Attaching package: ‘PerformanceAnalytics’

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Loading required package: quantmod
Loading required package: TTR
Registered S3 method overwritten by 'quantmod':
  method            from
  as.zoo.data.frame zoo 

library(tidyverse)

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library(tsibble)

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library(fable)

Loading required package: fabletools

Attaching package: ‘fable’

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library(feasts)

index = tq_index("SP500") %>% select(symbol, weight)

Getting holdings for SP500

index = index %>% filter(symbol != "-")
index

sum(index$weight)

[1] 0.9961429

data = tq_get(index$symbol, get = "stock.prices", from = "2022-01-01", to = "2024-03-29") %>% select(symbol, date, adjusted)

Warning: There were 2 warnings in `dplyr::mutate()`.
The first warning was:
ℹ In argument: `data.. = purrr::map(...)`.
Caused by warning:
! x = 'GEV', get = 'stock.prices': Error in getSymbols.yahoo(Symbols = "GEV", env = <environment>, verbose = FALSE, : Unable to import “GEV”.
HTTP error 400.
 Removing GEV.
ℹ Run ]8;;ide:run:dplyr::last_dplyr_warnings()dplyr::last_dplyr_warnings()]8;; to see the 1 remaining
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data = as_tsibble(data, key = symbol, index = date, regular = TRUE)
#data = fill_gaps(data) %>% fill(adjusted, .direction = "down")
#data = mutate(data, t = row_number())
#data = update_tsibble(data, index = t)

Split de datos

train = data %>% filter(date < "2024-03-03")
test = data %>% filter(date > "2024-03-04")

Modelos

ETS y ARIMA

sp500_arima_ets = train %>% model(arima = ARIMA(adjusted),
                                  ets = ETS(adjusted))

Warning: NaNs producedWarning: NaNs producedWarning: NaNs producedWarning: NaNs producedWarning: NaNs producedWarning: NaNs producedWarning: NaNs producedWarning: NaNs producedWarning: NaNs producedWarning: NaNs produced

sp500_arima_ets

ticker = "ABNB"
sp500_arima_ets %>% filter(symbol == ticker) %>% augment() |>
  ggplot(aes(x = t)) +
  geom_line(aes(y = adjusted, colour = "reales")) +
  geom_line(aes(y = .fitted, colour = "ajustados")) +
  labs(y = NULL,
    title = ticker
  ) +
  guides(colour = guide_legend(title = NULL))